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The slow-fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow-fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow-fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow-fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow-fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species.

Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species' life histories. Here, we use long-term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow-fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long-run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.

Host and pathogen dynamics are driven by seasonal variation, leading to complex epidemic patterns which are not well understood. Here, we linked demography and epidemiology in a single framework to reach a mechanistic understanding of disease dynamics in natural populations characterized by seasonality. We applied this approach to depict the interplay between a host, the wild boar, and a viral disease, African swine fever. This virus spreads in wild boar by direct‐contact among living individuals or though contacts with infected carcasses. In this system, both host and pathogen show seasonal patterns: survival and reproduction probabilities vary across the year in the wild boar, and virus persistence in the environment is affected by temperature which influences the speed of carcasses degradation. Using a stochastic individual‐based model, we showed that virus invasion success strongly varies according to the time of introduction due to the seasonal specific interaction between the virus and host. Furthermore, the shape of the following epidemic varies across seasons, with variation in speed and magnitude of the outbreak. Consequently, the host population response was also season‐specific, both regarding the speed of the decline and the change in population structure. Overall, our study highlights the inextricable connections between host, pathogen and the environmental dynamics, and the importance to consider each component to understand disease dynamics. [ABSTRACT FROM AUTHOR]

Climate change can influence populations of monogamous species by affecting pair‐bond dynamics. This study examined the impact of climate on widowhood and divorce, and the subsequent effects on individual vital rates and life‐history outcomes over 54 years in a snow petrel (Pagodroma nivea) population. We found that environmental conditions can affect pair‐bond dynamics both directly and indirectly. Divorce was adaptive, occurring more frequently after breeding failure and leading to improved breeding success. Divorce probabilities also increased under severe climatic conditions, regardless of prior breeding success, supporting the 'Habitat‐mediated' mechanisms. Overall, pair‐bond disruptions reduced subsequent vital rates and lifetime outcomes. Climate forecasts from an Atmosphere–Ocean General Circulation Model projected increased male widowhood rates due to decreased sea ice negatively affecting female survival, despite considerable uncertainty. These findings highlight the importance of environmentally induced changes in demographic and pair‐bond disruption rates as crucial factors shaping demographic responses to climate change. [ABSTRACT FROM AUTHOR]

Any average pattern observed at the population level (cross‐sectional analysis) may confound two different types of processes: some processes that occur among individuals and others that occur within individuals. Separating within‐ from among‐individual processes is critical for our understanding of ecological and evolutionary dynamics.The within‐individual centring method allows distinguishing within‐ from among‐individual processes and this method has been widely used in ecology to investigate both linear and quadratic patterns. Here we show that two alternative equations could be used for the investigation of quadratic within‐individual patterns. We explain the different assumptions and constraints of both equations. Reviewing the literature, we found that mainly one of these two equations has been used in studies investigating quadratic patterns. Yet this equation might not be the most appropriate in all circumstances leading to bias and imprecision.We show that these two alternative equations make different assumptions about the shape of the within‐individual pattern. One equation assumes that the within‐individual effect is related to an absolute process whereas the other assumes the effect arises from an individual relative process. The choice of using one equation instead of the other should depend upon the biological process investigated.Using simulations, we showed that a mismatch between the assumptions made by the equation used to analyse the data and the biological process investigated might led to flawed inference affecting output of model selection and accuracy of estimates. We stress that the equation used should be chosen carefully. We provide step by step guidelines for choosing an equation when studying quadratic pattern with the within‐individual centring approach. We encourage the use of the within‐individual centring method, promoting its relevant application for nonlinear relationships. [ABSTRACT FROM AUTHOR]

The cover image is based on the Original Article Direct and indirect estimates of dispersal support strong juvenile philopatry and male‐biased dispersal in a freshwater turtle species (Emys orbicularis), by Rémi Fay et al., https://doi.org/10.1111/fwb.14171..By Rémi Fay; Sébastien Ficheux; Arnaud Béchet; Aurélien Besnard; Pierre‐André Crochet; Raphaël Leblois; Alain Crivelli; Rémi Wattier and Anthony OlivierReported by Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

The article discusses that in Switzerland, kestrel bird nesting was stepped up in the late 1990s and early 2000s and for the past 15 years, many volunteers have been tracking nest boxes throughout the Middle East. , under the coordination of the Ornithological Station.

The slow-fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow-fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow-fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow-fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow-fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species.